Hi all
from Oz (Australia)First post on this list. I am a mine geo currently
doing some post-grad geostats study (Edith Cowan Uni in WA, hi Dr Ute, Prof.
Lyn!).Expanding on some very useful feedback from my Uni course director, I
would be interested in your learned "from the horse's mouth" comments (what,
why, how, when) regarding the bi-Gaussian assumption for Gaussian simulation and
the various means of checking it. I am slightly "mathematically
challenged", so if anyone could explain the whole thing without too much scary
maths, it would be much appreciated. I have Goovaerts' green geostats
bible, which is good stuff, but I'm trying to convert some of the maths to
English.Any comments from mining practitioners would be
interesting...CheersPerry CollierSenior Mine GeologistErnest
Henry Mine Xstrata Copper AustraliaPh:(07) 4769 4527Fax:
(07) 4769 4555E-mail: pcollier@...Web: http://www.xstrata.com

PO Box
527Cloncurry QLD 4824Australia

"I like rich people. I like
the way they live. I like the way I live when I'm with them..."From Roger
& Hammerstein's Sound of
Music

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Pierre Goovaerts

Well, as the author of the green bible I guess I should help out a little bit here... The key idea is that there exists an analytical expression that allows

Message 2 of 4
, Mar 23, 2005

Well, as the author of the "green bible" I guess I should help out a little bit here...

The key idea is that there exists an analytical expression that allows you to
compute a priori, for any threshold of a multigaussian random function,
the indicator semivariogram models. You only need to know the threshold
and the normal score semivariogram of the variable. Then, you just compare
the "expected" or "theoretically-derived" indicator semivariogram models
to the "empirical" or "derived from the data" ones.

Note that you don't even need to go through the burden of computing the
"theoretically-derived" indicator semivariogram models to know that the
underlying assumptions of the multigaussian model are not fulfilled.
In many situations, you will notice that your experimental indicator semivariograms
are not symmetric with respect to the median; for example the 0.1 decile
semivariogram might have a longer range than the 0.9 decile semivariogram.
This happens frequently since the low background values tend to be better
connected in space than the high values...

The next question is "what do we do with that?"... or in other words "How do we
know that the differences between expected and empirical indicator semivariograms
are significant". You could test it, but I don't think it's worth it in practice...
Well, cross-validation has taught me that even if the indicator semivariograms don't
look like expected under the multigaussian model, multigaussian kriging might
still give you better results than indicator kriging.. so it's hard to come up with
"cast-in-stone" rules regarding the relative merits of parametric and non-parametric
approaches.. but I am sure that everyone who has some experience with geostatistics
has already realized that.. As I often say during my short-course, geostatistics provides
you with a toolbox, and cross-validation and experience will teach you wich tools
to use in any particular situation...

First post on this list. I am a mine geo currently doing some post-grad geostats study (Edith Cowan Uni in WA, hi Dr Ute, Prof. Lyn!).

Expanding on some very useful feedback from my Uni course director, I would be interested in your learned "from the horse's mouth" comments (what, why, how, when) regarding the bi-Gaussian assumption for Gaussian simulation and the various means of checking it. I am slightly "mathematically challenged", so if anyone could explain the whole thing without too much scary maths, it would be much appreciated. I have Goovaerts' green geostats bible, which is good stuff, but I'm trying to convert some of the maths to English.

"I like rich people. I like the way they live. I like the way I live when I'm with them..."
From Roger & Hammerstein's Sound of Music

**********************************************************************
The information contained in this e-mail is confidential and is
intended only for the use of the addressee(s).
If you receive this e-mail in error, any use, distribution or
copying of this e-mail is not permitted. You are requested to
forward unwanted e-mail and address any problems to the
Xstrata Queensland Support Centre.
Support Centre e-mail: supportcentre@...
Support Centre phone: Australia 1800 500 646
International +61 2 9034 3710
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